Evaluating Interventions and Titrations Using Fasting Blood Glucose

A recent paper reported a computer-coded glycation method (“in-silico glycation”) to monitor daily average glucose (AG) and associated A1c using the fasting readings of each patient. ¹ Another publication discussed the importance of a similar personalized method to monitor A1c levels. ² Such real-time tracking of A1c provides clinical guidance that coordinate interventions and titrations with the chaotic blood glucose (BG) cycles creating an effective proactive progression to lower A1c levels. ³

We discuss a health care application using fasting BG to manage A1c for a pre-diabetic patient. Early morning fasting BG (AMG) was measured for seven months. Based on the initial sequence of levels, the computed glycation of fasting BG was scaled to the nearest prior A1c 5.8% (40 mmol/mol), and its “offset” set to zero. Note that offset is not critical to the trending evaluation of the computed profile.^1,3 The two parameters of the predictor are thus determined. Figure 1 shows the A1c tracking profile indicating that the offset should be corrected by −0.1% (−1.1 mmol/mol). Follow-up assays confirmed the final A1c level to be stationary at 5.5% (37 mmol/mol).

Figure 1.

Tracking A1c using fasting blood glucose glycation.

In Figure 1 the white squares track the A1c predictions, and the white triangles indicate the initial calibration levels for the linear predictor as well as the final A1c level, both from nearest dates (not shown). The significant downward trend was initiated by lifestyle changes as recommended by the patient’s recurrent cycle patterns. ³

In summary in-silico glycation of fasting BG levels enables a glucose meter to become an effective clinical tool to track and monitor the personalized impact on AG and A1c of designed interventions and titrations.